EP 4049190 A4 20231101 - METHOD AND SYSTEM FOR QUERY TRAINING
Title (en)
METHOD AND SYSTEM FOR QUERY TRAINING
Title (de)
VERFAHREN UND SYSTEM FÜR ABFRAGETRAINING
Title (fr)
PROCÉDÉ ET SYSTÈME DE FORMATION D'INTERROGATION
Publication
Application
Priority
- US 201962925930 P 20191025
- US 202062986903 P 20200309
- US 2020056824 W 20201022
Abstract (en)
[origin: US2021125030A1] The method for query training can include: determining a graphical representation, determining an inference network based on the graphical representation, determining a query distribution, sampling one or more train queries from the query distribution, and optionally determining a trained inference network by training the untrained inference network using the train query. The method can optionally include determining an inference query and determining an inference query result for the inference query using the trained inference network.
IPC 8 full level
G06N 5/02 (2023.01); G06F 16/55 (2019.01); G06N 3/09 (2023.01); G06N 5/022 (2023.01); G06N 7/01 (2023.01)
CPC (source: EP US)
G06F 16/55 (2019.01 - EP); G06N 3/04 (2013.01 - US); G06N 3/08 (2013.01 - US); G06N 3/09 (2023.01 - EP); G06N 5/022 (2013.01 - EP); G06N 7/01 (2023.01 - EP); G06F 16/2471 (2019.01 - US)
Citation (search report)
[I] CHECHETKA ANTON: "Query-Specific Learning and Inference for Probabilistic Graphical Models", THESIS CARNEGIE MELLON UNIVERSITY, 8 June 2011 (2011-06-08), pages 1 - 195, XP055820687, Retrieved from the Internet <URL:http://www.cs.cmu.edu/~antonc/publications/thesis-draft.pdf> [retrieved on 20210702]
Designated contracting state (EPC)
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR
DOCDB simple family (publication)
US 11157793 B2 20211026; US 2021125030 A1 20210429; CN 115280329 A 20221101; EP 4049190 A1 20220831; EP 4049190 A4 20231101; US 2022012562 A1 20220113; WO 2021081180 A1 20210429
DOCDB simple family (application)
US 202017077542 A 20201022; CN 202080090326 A 20201022; EP 20879670 A 20201022; US 2020056824 W 20201022; US 202117482896 A 20210923